题目:Blog Communities and Influential Bloggers 报告人:Huan Liu Associate professor Arizona State University. 时间:6月20日(星期五) 10:00-11:00 地点:蒙民伟楼404会议室 摘要:Blogging becomes a popular way for a Web user to publish information on the Web. Bloggers write blog posts, share their likes and dislikes, voice thei r opinions, provide suggestions, report news, and form groups in Blogosphere. Bloggers form their virtual communities of similar interests. Activities happe ned on Blogosphere affect the external world. One way to understand the develo pment on Blogosphere is to find influential blog sites. There are many non-inf luential blog sites which form "the long tail". Regardless of a blog site bein g influential or not, there are influential bloggers. Inspired by the high imp act of the influentials in a physical community, we study a novel problem of i dentifying influential bloggers at a blog site. Active bloggers are not necess arily influential. Influential bloggers can impact fellow bloggers in various ways. In this work, we discuss the challenges of identifying influential blogg ers, investigate what constitutes influential bloggers, present a preliminary model attempting to quantify an influential blogger, and pave the way for buil ding a robust model that allows for finding various types of the influentials. To illustrate these issues, we conduct experiments with data from a real-worl d blog site, evaluate multi-facets of the problem of identifying influential b loggers, and discuss unique challenges. We conclude with interesting findings and future work. 简历:Huan Liu is an associate professor of Computer Science and Engineering a t Arizona State University. He received his Ph.D. from University of Southern California, researched at Telecom Research Labs in Australia, and taught at Na tional University of Singapore. He has been a visiting scholar at Microsoft Re search Asia, a consultant of AOL, a summer faculty fellow at Motorola Research Lab and at Air Force Research Lab, and was invited to Google Faculty Summit ( Summer 2008). His research interests are in data/web mining, machine learning, social computing, and artificial intelligence. These include search and optim ization problems that arise in many real-world applications with high-dimensio nal data of disparate forms such as text categorization, streaming data summar ization, biomarker identification, and text/web mining. His research covers ef ficient search algorithms, semi-supervised models, spectral analysis methods, bias analysis, and experiment and evaluation methodologies. The research is be ing expanded to taxonomy-based group profiling, searching for influential blog gers in a community, information integration of multiple data sources, trust a nd reputation of multi-source information, and predicting high-cost patients i n healthcare domains. His well-cited publications include books, book chapters , encyclopedia entries as well as conference and journal papers. His former gr aduate students have been professors at research universities and employed by Amazon, Google, Microsoft, and Yahoo, among others. He is a co-organizer of th e International Workshop Series on Social Computing, Behavioral Modeling, and Prediction in Phoenix, AZ (SBP’08 and SBP’09), a conference co-chair of the 12th Pacific Asia Conference on Knowledge Discovery and Data Mining in Osaka, Japan (PAKDD’08), and a program committee co-chair of the SIAM International Conference on Data Mining (SDM’09 http://www.siam.org/meetings/sdm09) in Ren o Area, Nevada. |